A framework for use of imprecise categorization in developing intelligent systems
IEEE Transactions on Fuzzy Systems
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
An intelligent information retrieval approach based on two degrees of uncertainty fuzzy ontology
Advances in Fuzzy Systems - Special issue on Fuzzy Functions, Relations, and Fuzzy Transforms: Theoretical Aspects and Applications to Fuzzy Systems
Expert Systems with Applications: An International Journal
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Information retrieval is the important work of Supply Chain Management (SCM) on the Semantic Web. Ontology-based semantic retrieval is a hotspot of current research. In order to achieve fuzzy semantic retrieval, this paper applies a fuzzy ontology framework to information retrieval system in SCM. The framework includes three parts: concepts, properties of concepts and values of properties, in which property’s value can be either standard data type or linguistic values of fuzzy concepts. The semantic query expansion is constructed by order relation, equivalence relation and inclusion relation between fuzzy concepts defined in fuzzy linguistic variable ontologies. The application to retrieve customer and product information in supply chain shows that the framework can overcome the localization of other fuzzy ontology models, and this research facilitates the semantic retrieval of information through fuzzy concepts on the Semantic Web.